Multi-Sensor Data Fusion Approach for Kinematic Quantities

A theoretical framework to implement multi-sensor data fusion methods for kinematic quantities is proposed. All defined through the allow combination of signals obtained from position, velocity and acceleration sensors addressing same target, improvement in observation kinematics target. Differently several alternative methods, considered ones need no dynamic and/or error models operate can be implemented with low computational burden. In fact, they gain measurements by summing filtered versions heterogeneous quantities. particular, case position measurement, use filters finite impulse responses, all characterized throughout bandwidth, place straightforward time-integrative operators, prevents drift that typically produced offset low-frequency noise affecting data. simulated scenario shows adopted method keeps a indirectly an accelerometer affected equal 1 ppm on full scale, within few full-scale position. If digital output undergoes second-order time integration, instead, measurement would theoretically rise up 12n(n+1) scale at n-th discrete instant. The class offered proposed therefore interesting those applications which direct are poor accuracy one has also look improve tracking